Architect, Machine Learning
Ramesh Sridharan is an Architect, Machine Learning, at Manifold. In this capacity, he engages with clients to understand the challenges they are facing, and work with them to produce a strategy and execution plan for their AI goals.
Prior to Manifold, Ramesh led a machine learning engineering team at Vidado, a venture-backed software company that offers an enterprise-grade data extraction solution for paper documents. There, he led a team of engineers that developed the industry’s most accurate handwriting recognition and helped drive the company toward an AI-driven solution. In addition to training models and conducting computer vision research, he developed the company’s data acquisition and labeling strategy and implemented processes for accelerating ML research to production.
He also serves as a Lecturer at UC Berkeley, where his course Foundations of Data Science teaches hundreds of undergraduates the fundamentals of programming, data visualization, statistics, and machine learning.
Ramesh received his PhD in Computer Science from MIT, specializing in machine learning applied to medical imaging. He has a BS in Computer Science from UC Berkeley.
When not working on machine learning, Ramesh can be found enjoying the Bay Area’s natural beauty on a hike or bike ride, or in the kitchen baking or cooking.